Good morning, it’s Thursday. We’ve officially entered the cozy limbo between the holidays and the new year. Do I eat more cookies or lean into that “New Year, New Me” energy?
We recently interviewed Genmo CEO Paras Jain, covering everything from their groundbreaking generative video model, Mochi 1, to their strategic open-source bet, and Jain's bold vision for the future of creativity and generative AI.
Plus, the Forward Future 50 continues with the next batch of 2024’s biggest AI stories.
Alright, more cookies.
⚡️ AI BOOM TOWNS
Data Centers, Electricians, and the Rise of an A.I. Economy
The Recap: The small towns of Central Washington are undergoing rapid transformation as tech giants like Microsoft build massive data centers in the area, lured by the region's hydropower supply. This boom is attracting waves of electricians from across the country, reshaping the local economy and communities with high-paying jobs, soaring housing costs, and a focus on new infrastructure.
Massive data centers are being constructed to support AI development, requiring vast amounts of electricity and thousands of skilled electricians.
Electricians earn up to $2,800 a week after taxes, with Microsoft alone forecasting a need for 2,300 electricians in coming years.
In Quincy, property taxes from data centers have funded facilities like a $108 million high school, even as four in five students qualify for free lunch.
Median home prices in Douglas County have jumped 18% in a year, driven by demand from incoming workers and new construction.
State tax breaks mandate union labor for these projects, which has boosted local apprenticeships and diversified training opportunities.
The region’s hydropower grid is nearing its limit, sparking plans for new transmission lines and hopes for alternative energy sources like nuclear fusion.
Despite immediate economic benefits, locals worry about sustainability, with completed data centers requiring few permanent jobs.
Forward Future Takeaways:
The Central Washington data center boom highlights the intersection of rural transformation, labor dynamics, and the tech industry's insatiable demand for infrastructure. While the influx of high-paying jobs is uplifting some families, rising housing costs and energy constraints hint at potential challenges ahead. As AI drives further demand, balancing economic growth with equitable, sustainable development will be critical for the region’s future. → Read the full article here.
🏆 2024 HIGHLIGHTS
Forward Future 50: The Top AI Stories of 2024
#43 AI Drones Transforms Search and Rescue: SARDO, an AI-powered drone software, accelerated search and rescue missions by identifying subtle visual cues, reducing search times, and saving lives in remote terrains.
#41 Adobe Launches AI Video Tools: Adobe unveiled Firefly Video Model at MAX 2024, enabling AI-powered text-to-video creation, seamless editing, and lip-sync dubbing—offering commercially safe, creative solutions.
#40 AI Combats Wildlife Crime: AI tools, including smart sensors and satellite analysis, revolutionized wildlife crime prevention by detecting poaching, illegal logging, and fishing with real-time alerts and predictive modeling.
#38 CRISPR + AI Reshape Medicine: AI accelerated CRISPR-based gene editing by improving precision, predicting outcomes, and designing novel proteins—reshaping healthcare, agriculture, and sustainability.
📻️ Tune in tomorrow for the next batch of top stories from 2024.
👾 FORWARD FUTURE ORIGINAL
Reimagining Creativity: Paras Jain on Genmo’s Vision and Future of Generative AI
Jain's professional journey began in the autonomous vehicle industry, where he was a founding engineer at DeepScale, a startup later acquired by Tesla. Reflecting on his transition from self-driving technology to generative AI, Jain explained: "The methodologies and systems thinking from autonomous driving deeply influenced our approach at Genmo. Understanding complex data pipelines and scaling models efficiently were lessons directly applicable to AI-driven video generation."
His academic and professional trajectory, from scaling natural language models during his PhD to witnessing the transformative power of diffusion models pioneered by his brother and co-founder, Ajay Jain, was marked by moments of revelation. “It was in 2020, when I first saw the power of transfer learning applied to code generation. That week-long experiment outperformed months of hand-tuned efforts. It was a revelation—AI could accelerate human creativity,” he recounted.
Innovations in AI Video Generation
Genmo’s October launch of Mochi 1 introduced a groundbreaking generative video model. Unlike existing tools like Runway or MidJourney, Genmo’s approach prioritizes “motion reasoning” to create videos with dynamic and realistic movement.
"The feedback was overwhelmingly clear," Jain noted. "Users want videos that feel alive, where motion tells a story, even if the resolution is slightly less polished."
The model’s success is rooted in its ability to generate realistic, fluid actions and expressions, crossing the uncanny valley and setting a new standard for AI-driven video content. → Continue reading here.
🔬 RESEARCH PAPERS
GaussianProperty: Mapping Properties to 3D Gaussians for Simulations and Robotics
Researchers introduced GaussianProperty, a novel training-free framework that assigns physical material properties to 3D Gaussians, enhancing applications in computer vision, simulations, and robotics. By combining the segmentation ability of SAM with GPT-4V(ision)’s recognition, the system infers physical properties from 2D images and projects them onto 3D models via a voting mechanism.
These annotated 3D Gaussians enable physics-based simulations using the Material Point Method (MPM) and predict safe grasping forces for robots. Experiments demonstrate its utility in material segmentation, dynamic simulations, and robotic grasping, paving the way for advanced physical reasoning in visual data. → Read the full paper here.
📽️ VIDEO
Anthropic Drops an Insane New Paper…
In case you missed it, Matt covered Anthropic’s groundbreaking research, exposing how AI models can fake alignment—appearing compliant during training but reverting to their original goals once deployed. This raises serious concerns about AI safety as models grow more deceptive and sophisticated. Get the full scoop! 👇
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